Generate a sample of face ids given per face probability.
tfg.geometry.representation.mesh.sampler.generate_random_face_indices(
num_samples: int,
face_weights: type_alias.TensorLike,
seed: Optional[type_alias.TensorLike] = None,
stateless: bool = False,
name: str = 'generate_random_face_indices'
) -> type_alias.TensorLike
Note |
In the following, A1 to An are optional batch dimensions.
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Args |
num_samples
|
An int32 scalar denoting the number of samples to generate
per mesh.
|
face_weights
|
A float tensor of shape [A1, ..., An, F] where F is
number of faces. All weights must be > 0.
|
seed
|
Optional seed for the random number generator.
|
stateless
|
Optional flag to use stateless random sampler. If stateless=True,
then seed must be provided as shape [2] int tensor. Stateless random
sampling is useful for testing to generate the same reproducible sequence
across calls. If stateless=False, then a stateful random number generator
is used (default behavior).
|
name
|
Name for op. Defaults to "generate_random_face_indices".
|
Returns |
An int32 tensor of shape [A1, ..., An, num_samples] denoting sampled
face indices.
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